System and method for performing virtual surgery

ABSTRACT

A method and system are presented for performing virtual surgery simulations. The computer system includes a processor and a memory. The method includes receiving user input from a user via a user interface. The user input includes input representing surgical operations or non-surgical invasive procedures. The method also includes processing the user input and utilizing the input to generate or modify a computational model. The method also includes running simulations using the computational model in accordance with the user input. After running the simulations, the method further includes determining results from the simulations. The results correspond to probable effects or outcomes of performing real life surgical operations or non-surgical invasive procedures corresponding to the user input. Last, the method includes presenting the results to the user via the user interface.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims benefit under 35 U.S.C.§ 120 to U.S. application Ser. No. 14/211,452, filed Mar. 14, 2014,titled “SYSTEM AND METHOD FOR PERFORMING VIRTUAL SURGERY” by Mark B.Ratcliffe et al., which claims benefit of prior application U.S.Provisional Application No. 61/801,000, filed Mar. 15, 2013, titled“SYSTEM AND METHOD FOR PERFORMING VIRTUAL SURGERY” by Mark B. Ratcliffeet al. Both applications are herein incorporated by reference in theirentireties for all purposes.

TECHNICAL FIELD

The disclosed embodiments relate generally to computational modeling andsimulations in computer systems.

BACKGROUND

Currently, practicing surgeons, clinicians, medical device engineers,scientists and trainees work with physical models or cadavers whendeveloping novel surgical operations and non-surgical invasiveprocedures, training to perform surgeries or non-surgical invasiveprocedures, or developing instruments or implants related to thosesurgeries or non-surgical invasive procedures. Physical simulators madeof rubber/plastic material in a “shoebox” are used by educators toevaluate how a trainee sutures or cuts. However, physical simulators andmodels have many limitations. More specifically, physical models madefrom materials such as plastic, rubber, latex, foam, metal, ceramics, orother manufactured materials do not provide the ability to fullyreplicate the consistency, texture, and physical properties of humantissue. Cadavers have many limitations as well. More specifically,cadavers do not allow the ability to compare the effects of oneprocedure with another procedure given that no two cadavers areidentical. Additionally, a cadaver cannot fully replicate living humantissue due to the change in physical properties that occurs during thepreparation and preservation of the tissue to prevent decomposition andthe inherent inability for a cadaver to mimic living tissue such asmuscle, which contracts. Thus, there exists a need for usingcomputational modeling to simulate surgical operations and non-surgicalinvasive procedures. These same limitations to physical models andcadaver specimens affect medical device engineers in the development ofnew or refinement of existing instruments or implants. Additionally,practicing surgeons develop their surgical plan for an individualpatient using “historical” information based upon their personalexperience gained during training or while in practice from similarpatients or published studies in medical literature reporting theoutcome of a procedure from similar patients. The systems and methodpresented in the present disclosure allow for clinicians to predict theoutcome of their surgery or non-surgical invasive procedure in advance,using computational modeling to simulate surgical operations andnon-surgical invasive procedures, for their individual patients.

SUMMARY

In one aspect of the present disclosure, a method to be performed by acomputer system is provided. The computer system includes a processorand a memory. The method includes receiving user input from a user via auser interface. The user input includes input representing surgicaloperations or non-surgical invasive procedures. The method also includesprocessing the user input and utilizing the input to generate or modifya computational model. The method also includes running simulationsusing the computational model in accordance with the user input. Afterrunning the simulations, the method further includes determining resultsfrom the simulations. The results correspond to probable effects oroutcomes of performing real life surgical operations or non-surgicalinvasive procedures corresponding to the user input. Last, the methodincludes presenting the results to the user via the user interface.

In another aspect of the present disclosure, a system is provided. Thesystem includes a user interface and a computer. The computer includes aprocessor and memory, and is configured to receive user input from theuser interface, wherein the user input includes input representingsurgical operations or non-surgical invasive procedures. The computer isfurther configured to process the user input and utilize the input togenerate or modify a computational model. The computer is furtherconfigured to run simulations using the computational model inaccordance with the user input. In addition, the computer is configuredto also determine results from the simulations, wherein the resultscorrespond to probable effects or outcomes of performing real lifesurgical operations or non-surgical invasive procedures corresponding tothe user input. Last, the computer is configured to present the resultsto the user via the user interface.

In some embodiments of the present disclosure, processing the user inputincludes pre- and post-processing of data provided to a solver module.

In some embodiments, the user input is pre-processed before beingreceived. In some embodiments, the method is performed dynamically whilethe user is performing steps of a surgery or non-surgical invasiveprocedure simulation. In some embodiments, the user input includes inputfrom a keyboard, mouse, camera, microphone, tablet, cellular phone, anyhandheld device, or any haptic device capable of performing motions orfunctions representing surgical operations or other non-surgicalinvasive procedures that effect anatomic structures. In someembodiments, the user input is sent via a web browser or any applicationwith access to the Internet. In some embodiments, processing the userinput includes performing one more actions in a queue, utilizing theuser input to generate or modify a computational anatomic model, thecomputational anatomic model being divided into one or more partsincluding a geometric mesh, material properties, and loading conditions.In some embodiments, the method further includes converting clinicalimaging or information, such as blood pressure, height, weight, and labresults, into data and representing the data in a computational modelincluding a geometric mesh, material properties, and loading conditions.In some embodiments, the user input includes surgical language andprocessing the user data includes converting, via a clinical translationmodule, the surgical language to changes or discrete values in ageometric mesh, material properties, or loading conditions of acomputational model. In some embodiments, determining results of thesimulation includes converting output geometric mesh, materialproperties, or other data with associated physical properties intosurgical language. In some embodiments, the method further includesvalidating the user information submitted from the user system to theclinical system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is an overview of an example system for implementing variousmethods of the present disclosure.

FIG. 1B is a flow diagram illustrating an overview of an example processimplemented with the example system in FIG. 1A, in accordance withvarious embodiments of the present disclosure.

FIGS. 2A and 2B illustrate various aspects of a real heart, inaccordance with various embodiments of the present disclosure.

FIGS. 2C and 2D illustrate examples of geometric mesh modelscorresponding to the various aspects of a real heart presented in FIGS.2A and 2B, in accordance with various embodiments of the presentdisclosure.

FIGS. 3A-3D depicts an example of a typical surgical procedure formitral valve repair, in accordance with various embodiments of thepresent disclosure.

FIGS. 4A-4F are examples of simulating a mitral valve repair procedureusing computational modeling, in accordance with various embodiments ofthe present disclosure.

FIG. 5 illustrates an example of human knee, in accordance with variousembodiments of the present disclosure.

FIG. 6A illustrates a simulated model of a human knee, in accordancewith various embodiments of the present disclosure.

FIG. 6B illustrates a simulated model of a human knee that has undergonea medial meniscectomy, in accordance with various embodiments of thepresent disclosure.

FIG. 7 is a flow chart illustrating an exemplary process for performingvirtual surgery, in accordance with various embodiments of the presentdisclosure.

FIG. 8 is a block diagram illustrating an example of a computer systemcapable of implementing various processes described in the presentdisclosure.

Like reference numerals refer to corresponding parts throughout thedrawings.

DESCRIPTION OF EMBODIMENTS

It will be understood that, although the terms “first,” “second,” etc.may be used herein to describe various elements, these elements shouldnot be limited by these terms. These terms are only used to distinguishone element from another. For example, a first contact could be termed asecond contact, and, similarly, a second contact could be termed a firstcontact, which changing the meaning of the description, so long as alloccurrences of the “first contact” are renamed consistently and alloccurrences of the second contact are renamed consistently. The firstcontact and the second contact are both contacts, but they are not thesame contact.

Definitions

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the claims. Asused in the description of the embodiments and the appended claims, thesingular forms “a”, “an” and “the” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willalso be understood that the term “and/or” as used herein refers to andencompasses any and all possible combinations of one or more of theassociated listed items. It will be further understood that the terms“comprises” and/or “comprising,” when used in this specification,specify the presence of stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof.

As used herein, the term “if” may be construed to mean “when” or “upon”or “in response to determining” or “in accordance with a determination”or “in response to detecting,” that a stated condition precedent istrue, depending on the context. Similarly, the phrase “if it isdetermined [that a stated condition precedent is true]” or “if [a statedcondition precedent is true]” or “when [a stated condition precedent istrue]” may be construed to mean “upon determining” or “in response todetermining” or “in accordance with a determination” or “upon detecting”or “in response to detecting” that the stated condition precedent istrue, depending on the context.

As used herein, the term “user” is used interchangeably with “surgeon.”In addition, as used herein, the term “user” is also usedinterchangeably with “trainee,” “clinician,” “engineer,” and“scientist.”

As used herein, the term “surgical language” is used interchangeablywith “medical language.” As used herein, the term “surgical language” isintended to mean the system by which physicians or surgeons or those inpractice or development of medicine use to communicate or acquirethought or information. This includes letters, acronyms, words, symbols,signs, images, photographs, graphs, numbers, statistics and diagrams andother visual representations of information. It also includes sounds,tactile sensations, smell, and taste.

As used herein, the term “computational model” is intended to describeany set of mathematical equations, numerical methods, algorithms,symbolic computation, or manipulation of mathematical expressions ormathematical objects that can be used to describe or represent thephysical mechanics or biology of the surgery to be studied. These modelscan be stochastic, deterministic, steady-state, dynamic, continuous ordiscrete.

As used herein, the term “medical imaging” is used interchangeably with“clinical imaging.” As used herein, “medical imaging” is intended todescribe any tool and the images generated by those tools that describeor quantify anatomic features, e.g. x-rays, computed tomography (CT)scans, magnetic resonance imaging (MM), and ultrasound.

As used herein, the term “surgery” is used interchangeably with“surgical operation.”

As used herein, the term “non-surgical invasive procedure” is usedinterchangeably with “medical intervention.” As used herein, the term“non-surgical invasive procedure” is used interchangeably with“interventional procedures.” In addition, as used herein, the term“non-surgical invasive procedure” is used interchangeably with“minimally invasive procedure.”

As used herein, the terms “surgery” and “non-surgical invasiveprocedure” are intended to describe any set of actions that altersanatomy directly or indirectly. In addition, as used herein, the terms“surgery” and “non-surgical invasive procedure” include actions involvedin the development of an implant, device, or product that alters anatomydirectly or indirectly. An example of direct alteration of anatomyincludes the use of a surgical instrument to cut or modify tissue. Anexample of indirect alteration of anatomy includes the use ofmedications that increase the strength of heart muscle contraction orincreases the bone mineral density of the skeleton.

As used herein, the terms “surgery” and “non-surgical invasiveprocedure” are intended to describe any set of actions performed by auser that would require or be expected to require informed consent froma patient if performed or used clinically, regardless of whether or notthe present use of the present disclosure is in a clinical setting.

As used herein, the distinction between a surgery and a non-surgicalinvasive procedure reflects the difference in visibility of the anatomythat is expected to be available to the user. In a surgery, directvisualization is used more than indirect visualization. In anon-surgical invasive procedure, indirect visualization is used morethan direct visualization. In a scenario where direct visualization andindirect visualization are used equally, the user's activity isconsidered both a surgery and a non-surgical invasive procedure. Directvisualization reflects a direct optical pathway between the anatomy andthe user and in some cases will include optics to assist withmagnification or visualization. Indirect visualization reflects the useof an intermediate tool such as camera, fluoroscopy, CT, MRI orultrasound where the user does not have a direct optical pathway to theanatomy.

As used herein, the term “solver” is used interchangeably with “solvermodule” and is intended to describe any set of numerical methods thatare used to represent true physical phenomena such as Newton's Laws ofMotion that provides sufficient accuracy to reflect clinical reality.The “finite element” approach is one such example that can be used inone embodiment of the present disclosure. The present disclosure is notrestricted to the use a “finite element” based solver. In someembodiments, the solver module uses numerical methods of simulation suchas finite difference, finite volume, finite element, ArbitraryLagrangian-Eulerian, Navier-Stokes, or Conservation Element & SolutionElement methods for fluid modeling.

As used herein, the action of “alteration of anatomy” refers to anyaction that can be represented as a change to a description of ageometric mesh, a material property, or any loading conditions.

As used herein, the term “geometric mesh” refers to any generateddescription that describes or defines the physical shape, micro- andmacro-structure, or form of one or more anatomic structures.

As used herein, the term “material property” refers to any descriptionof the physical characteristics of the anatomy described by thegeometric mesh in response to physical loads. In addition, as usedherein, “material property” also refers to the response topharmacologic, electrical, magnetic, or heating or coolinginterventions. In addition, as used herein, “material property” alsorefers to any characteristic of anatomy that can be represented asphysical changes, whether directly or indirectly through biologicalchanges.

As used herein, the term “loading condition” refers to any descriptionof the physical loads applied to or experienced by the anatomy. Inaddition, as used herein, the “loading condition” includes anydescription of pharmacologic, electrical, magnetic, or heating orcooling interventions.

As used herein, the term “clinical information” refers to medicalimaging, laboratory results such as serum potassium or calcium levels,physical examination results such as blood pressure, height, patienthistory such as occupation, use of tobacco products, and any additionalclinical data describing a patient that can be represented as a changeto the anatomy through a description of a geometric mesh, a materialproperty, or a loading condition.

As used herein, the term “patient” refers to both an entire individualas an organism as a whole as well as any subset of the patient's anatomysuch as a patient's organ system (e.g., cardiopulmonary systemreflecting the heart and lungs and the associated connective tissue), anindividual organ (e.g., a heart), a substructure of an organ (e.g. aheart valve), a substructure of a substructure (e.g. a leaflet of aheart valve), or a substructure of a substructure of the substructure(e.g. collagen bundle of a leaflet of a heart valve). There is no limitto the restriction to minimum size of the subset of the anatomy as thesize is defined by the user's request and anatomy of interest.

Reference will now be made in detail to various embodiments, examples ofwhich are illustrated in the accompanying drawings. In the followingdetailed description, numerous specific details are set forth in orderto provide a thorough understanding of the present disclosure and thedescribed embodiments. However, the present disclosure may be practicedwithout these specific details. In other instances, well-known methods,procedures, components, and circuits have not been described in detailso as not to unnecessarily obscure aspects of the embodiments.

For example, the techniques of the present disclosure will be describedin the context of fragments, particular servers and encoding mechanisms.However, it should be noted that the techniques of the presentdisclosure apply to a wide variety of different fragments, segments,servers and encoding mechanisms. In the following description, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present disclosure. Particular example embodimentsof the present disclosure may be implemented without some or all ofthese specific details. In other instances, well known processoperations have not been described in detail in order not tounnecessarily obscure the present disclosure.

Various techniques and mechanisms of the present disclosure willsometimes be described in singular form for clarity. However, it shouldbe noted that some embodiments include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. For example, a system uses a processor in a variety ofcontexts. However, it will be appreciated that a system can use multipleprocessors while remaining within the scope of the present disclosureunless otherwise noted. Furthermore, the techniques and mechanisms ofthe present disclosure will sometimes describe a connection between twoentities. It should be noted that a connection between two entities doesnot necessarily mean a direct, unimpeded connection, as a variety ofother entities may reside between the two entities. For example, aprocessor may be connected to memory, but it will be appreciated that avariety of bridges and controllers may reside between the processor andmemory. Consequently, a connection does not necessarily mean a direct,unimpeded connection unless otherwise noted.

EXAMPLE EMBODIMENTS

FIG. 1 illustrates a general overview of an example system (100) forimplementing various methods of the present disclosure. In particular,FIG. 1A describes a user accessing the Internet or Web (104) using acomputer (102) configured with a web browser to interact with anothercomputer configured as a server (106) containing modules required forfulfilling the user's simulation request.

FIG. 1B is a flow diagram illustrating an overview of an example process(120) implemented with the example system in FIG. 1A. In this example,the user provides patient information including cardiac pressures andimaging data such as MM (122) to the server. Once the data is receivedby the server, a computational model is created (124). In someembodiments, the computational model is a finite element model. Theserver provides information back to the user that will allow the user toperform virtual surgery (126). This is done using a graphical userinterface (GUI). Once the user has completed the virtual surgery, thedata is sent back to server where pre- and post-operative assessment isobtained through finite element analysis (128). The server then providesdata back to the user to detail the mechanical effect of virtual surgeryand the change in key mechanical pressures is presented (130).

According to various embodiments, virtual surgery simulations are basedupon the use of a prototypical source model, e.g., a three-dimensional(3-D) computational model representing a physical object, such as anindividual patient or a hypothetical patient made from averages. In someembodiments, the 3-D model contains one or more geometric meshes,material properties, and loading conditions. In some embodiments,parametric analysis is performed by changing the mesh geometry (alteringthe shape of the patient) or adding or removing the mesh geometry. Insome embodiments, changing the assigned material properties (alteringthe stiffness/softness of the tissue) is performed. In some embodiments,changing the loading conditions (e.g. blood pressure) is performed. Insome embodiments, small, directional increments in the geometric mesh,material properties, or loading conditions are performed followed byobservations. Parametric analysis in this way allows for understanding,in general terms, of the consequences or benefits of an action. Forinstance, if a heart is to be resized, the starting point would be anormal heart. Then, incrementally, the heart is adjusted to be smallerand smaller or bigger and bigger. Another example is a spine fusion.With parametric analysis, differences between a one or two-level fusioncan be readily observed. Another example is a meniscectomy of the knee.With parametric analysis, the optimal amount of meniscus to be removedcan be readily observed. Various surgical operations and othernon-surgical invasive procedures and devices can be simulated in thisway.

The following example illustrates an exemplary embodiment of the presentdisclosure. In this embodiment, the user is a practicing surgeoninterested in determining the effects of performing a mitral valverepair on a specific patient. The surgeon begins by taking a MRI of thepatient's heart in the pre-operative state and then sends it to theserver along with relevant patient information such as age, bloodpressure, and current medications (122). This is performed using a webbrowser (102). This data is received by the server (106) via theInternet (104) and processed by a clinical translation module. Themodule recognizes that the mitral valve repair requires a computationalmodel of the left ventricle and mitral valve. MRI data is sent from the“clinical translation module” to an “information integration module”where a geometric mesh representing the left ventricle and mitral valveis created. The geometric mesh is then assigned material propertiesbased upon both values in the MRI and a known database of materials inclinical translation module. The age, blood pressure and currentmedications are used to further refine the material properties andestablish the loading conditions for the computational model. Thisprocess generates a finite element model (124) which is then shown tothe surgeon via a user interface. Through this interface, the surgeonperforms the mitral valve repair, selecting the portion of the posteriormitral valve leaflet to be excised, the manner in which the remain freeends of the leaflet are sutured, and then the manner in which anannuloplasty ring is implanted and sutured (126). In this example, thesurgeon uses the graphical interface to replicate the surgeryillustrated in FIG. 3. The surgeon will identify the mitral valve (300)including the anterior (306) and posterior (308, 312, and 310) leaflets.In this example patient, the middle section of the posterior leaflet isprolapsing and causing the valve to leak (mitral regurgitation). Thesurgeon uses a scalpel (305) and forceps (302) to excise out thetriangular section of the mitral valve prolapse (312) along the dottedlines. The resulting triangular defect between the left (308) and right(310) scallops of the posterior mitral leaflet caused by the excision ofthe prolapsing segment are identified. The surgeon places sutures (322)to bring the cut edges of the leaflet together. The repaired leaflet(308, 310) after the sutures (322) have been tied. The surgeon thenapplies a supporting or buttressing “annuloplasty” ring (360, 362). Inthis example, the surgery is expected to result in a repaired valve thatis competent and functional.

The surgeon's actions are stored in a queue and sent back to the server(106) for further processing. The clinical translation module translatesthe queue of actions into a series of modifications to a geometric mesh,material property, and/or loading condition. The translation isperformed by a database within the clinical translation module, andactions by the surgeon that are outside of the database are submitted tothe information integration module for further processing. Theinformation integration module will either combine imaging data or otherclinical information to determine how the action in the queue will berepresented as changes to a geometric mesh, material property, and/orloading condition. If the information integration module is unable todetermine the optional representation needed for the solver module, thesurgeon's action is flagged for human evaluation and modification. Afterthe surgeon's input has fully been processed, it is provided to thesolver module. The solver module uses realistic mathematical simulationto perform the surgery as described by the surgeon. This entire sequenceof steps (128) results in a mathematical representation of the surgicaloutcome. The clinical translation module then converts the output fromthe solver module into surgical language. This is then presented to thesurgeon (130). In this example, the outcome will be presented as avisual animation of the beating left ventricle and motion of the mitralvalve before and after surgery along with changes in key mechanicalparameters for this surgery (130). In this example, the clinicaltranslation module will report cardiac outcome parameters based upon thelocation of the surgery such as the force across the sutures, the stressto the fibers of the muscle at the different regions of the leftventricle, as well as the pressure and stress to the mitral valveleaflets.

In some embodiments, parametric analysis is requested by the clinicaltranslation module to be performed by the solver module. After the userperforms virtual surgery (126), the clinical translation module willevaluate the outcome of small perturbations in the surgeon's technique.For example, in some embodiments different annuloplasty rings (362) fromdifferent device manufacturers made from different materials or shapescan be simulated with the change in outcome, if any, reported to thesurgeon (130). In some embodiments, the number of sutures (322) used isincreased or decreased. In some embodiments the amount of the leaflet tobe removed (312, dashed lines) is increased or decreased. In someembodiments, the clinical translation module will continue to testadditional perturbations and report the outcome of the surgeon's plan incomparison to the optimal approach as determined through this iterativeparametric analysis.

In another embodiment, a similar set of steps can be used to evaluate atrainee and determine if the steps made by the trainee in surgery (126)result in a clinically successful outcome. In some embodiments, surgicalcomplications will be introduced such as a failure of a suture (322) todetermine if the trainee will recognize the problem and make theappropriate surgical maneuvers to correct the failure.

In some embodiments, the user is a device engineer or scientist and asimilar set of steps can be used to evaluate the optimal conditions forimplanting a device or the optimal characteristics of a device.

In some embodiments, the user is interested in understanding the effectsof a surgery generally for an improved understanding of the actions ofspecific alteration of anatomy. In some embodiments, there is nospecific patient of interest, no specific device or instrumentation ofinterest, and no assessment of skills to be performed.

In some embodiments, the user can alter the anatomy in real-life througha surgical operation or a non-surgical invasive procedure. In someembodiments, the user will use the present disclosure to evaluate thetechnical difficulty of the approach to anatomic alteration. In someembodiments, the user will use the present disclosure to determine theportions of the procedure which are best achieved through a surgery anda non-surgical invasive procedure.

In some embodiments, the data submitted by the user (122) containsadditional types of clinical imaging such as CT scan or additionalinformation or data in surgical language. In some embodiments, the datasubmitted by the user excludes cardiac pressures and MM. The presentdisclosure is not restricted to a requirement for input of cardiacpressures and MM. In some embodiments, the user will submit a completeexisting computational model and bypass the need for the server (106) tocreate a model (124). In some embodiments, the user will submit anincomplete computational model containing one or more geometric meshes,material properties, or loading conditions.

In some embodiments, the user input is performed using a keyboard ormouse. In some embodiments, other input may be used including point andclick with a mouse, voice activated input, typing input via a keyboard,scanned input via cameras or motion sensors, or input from handhelddevices such as a smart phone or tablet PC. Input can also be made viaany haptic device capable of performing motions or functionsrepresenting surgical operations or other interventions or proceduresthat affect anatomic structures. The motions or functions are capturedand stored for processing or transmission. In some embodiments, there isa direct translation of the input actions to the computational model.

According to various embodiments, the system providing the clinicaltranslation module, through a combination of automated tools and/orhuman labor, translates the user input representing virtual surgicaloperations into input for the solver module. In some embodiments, thisincludes describing in surgical language, via a text or graphicalinterface, the planned procedure.

According to various embodiments, the system providing the clinicaltranslation module, through a combination of automated tools and/orhuman labor, translates the output of the solver module representing theoutcome or result of virtual surgical operations into surgical language.In some embodiments, this reporting of information in surgical language,occurs via a text or graphical interface.

According to various embodiments, data available to the clinicaltranslation module is made available to the information integrationmodule for additional pre- and post-processing before input is providedto the solver module or output is provided to the user.

According to various embodiments, the system providing the informationintegration module, through a combination of automated tools and/orhuman labor, translates the user input representing “clinicalinformation” into alterations of a geometric mesh, a material property,or a loading condition.

In some embodiments, clinical imaging data available to the informationintegration module lacks sufficient visual fidelity to identify anatomicstructures of importance. One such example would be the intermeniscalligaments that connect the medial meniscus and lateral meniscus of theknee. In some embodiments, the information integration module willgenerate a geometric mesh, material property, or a loading conditionrepresenting structures that are known to exist despite the absence ofthe structure on imaging based upon landmarks that are visible. One suchexample would be generating a computational model of the intermeniscalligaments based upon the location of the anterior horn of the medialmeniscus and lateral meniscus. In some embodiments, the addition ofcomputational models of anatomic structures not visible in the imagingdata occurs without additional user input. In other embodiments, theaddition of computational models of anatomic structures not visible inthe imaging data occurs with user input.

In some embodiments, clinical information necessary for a computationalmodel used by the solver module is not available to the informationintegration module. One such example would be a user that has notspecified the blood pressure, or a height, or a weight as input. In someembodiments, the information integration module will provide the missingclinical information necessary for a computational module used by thesolver module. In some embodiments, the substituted information reflectsa 50th percentile value. In some embodiments, the substitutedinformation reflects a 5th percentile value. In some embodiments, thesubstituted information reflects a 95th percentile value. In someembodiments, the substitution of clinical information is performedwithout additional user input. In other embodiments, the substitution ofclinical information occurs with user input.

According to various embodiments, the system providing the informationintegration module exchanges data to translate the user input intoalterations of a geometric mesh, a material property, or a loadingcondition or into a surgical language that can be processed by theclinical translation module.

The following example illustrates another exemplary embodiment of thepresent disclosure. In this embodiment, the user is a trainee interestedin understanding the effects of performing a medial meniscectomy in theknee without a specific patient in mind or surgical goal. In thisembodiment, the trainee uses a pre-existing template representing acomputational model of the knee and does not need to upload any newinformation to the server nor does the server need to create a newcomputational model. Using the standardized template computational modelof the knee, the trainee identifies the geometric mesh representing themedial meniscus and uses the user interface to remove this structure.The trainee then selects the loading condition of a standing patient foranalysis. The system mathematically identifies the resulting varusmoment and presents the output to the user in surgical language via theuser interface.

In some embodiments a template computational model represents an averagepatient. In other embodiments, the template computational modelrepresents a patient with anatomy that does not have an averagegeometric mesh, material property, or loading condition. One suchexample would be a patient with a disease.

In some embodiments, the user will alter a geometric mesh directly todetermine the effects of that action. In some embodiments, thealteration is done using surgical language. In some embodiments, thealteration is done through manipulation of a geometric mesh directlythrough the user interface.

In some embodiments, the user will alter a material property directly todetermine the effects of that action. In some embodiments, thealteration is done using surgical language. In some embodiments, thealteration is done through manipulation of a material property directlythrough the user interface.

In some embodiments, the user will alter a loading condition directly todetermine the effects of that action. In some embodiments, thealteration is done using surgical language. In some embodiments, thealteration is done through manipulation of a loading condition directlythrough the user interface.

FIGS. 2A and 2B are exemplary drawings of the various aspects of a realheart, in accordance with various embodiments of the present disclosure.FIG. 2A shows the outside of the left ventricle (200) and in this casealso shows an area of heart attack (myocardial infarction (MI) where theMI (206) is surrounded by a border of poorly contractile heart muscle(204) and the normal undamaged heart muscle (202). FIG. 2B shows theinside of the left ventricle (220). The mitral valve is the inflow valveto the left ventricle and FIG. 2B further shows the muscular connectionsor papillary muscles (208) by which the valve is connected to the leftventricular wall.

FIGS. 2C and 2D illustrate examples of geometric mesh models similar tomodels that would be created by exemplary systems such as system 100 inFIG. 1. In this exemplary case, FIGS. 2C and D correspond to the variousaspects of a real heart presented in FIGS. 2A and 2B, in accordance withvarious embodiments of the present disclosure. Specifically, as in FIG.2A, the mesh model in FIG. 2C shows the area of myocardial infarction(206), surrounded by a border of poorly contractile heart muscle (204)and beyond that the normal undamaged heart muscle (202). As in FIG. 2B,FIG. 2D shows the inside of the left ventricle (220) where in this casethe muscular connections to the mitral valve or papillary muscles areseen (208) with their connections (chordae) to the mitral valve at thetop of the left ventricle.

FIGS. 3A-3D illustrate an example of the steps involved in a typicalcardiac surgical procedure, in accordance with various embodiments ofthe present disclosure. In this exemplary case, a mitral valve repairprocedure is illustrated. The illustrations show the mitral valve (300)including the anterior (306) and posterior (308 and 310) leaflets. Inthis case, the middle section of the posterior leaflet is prolapsing andcausing the valve to leak (mitral regurgitation). In FIG. 3A, thesurgeon is performing a mitral valve repair procedure to repair themitral valve prolapse (312). Specifically, FIG. 3A shows the surgeongrasping the prolapsing segment (312) of the posterior leaflet of thevalve (308, 310) with forceps (302). A scalpel (304) is being used toexcise a triangular section (dotted lines) of the prolapsing segment(312). FIG. 3B shows the triangular defect between the left (308) andright (310) scallops of the posterior mitral leaflet caused by theexcision of the prolapsing segment. In this case, sutures (322) are nowin place to bring the cut edges of the leaflet together. FIG. 3C showsthe repaired leaflet (308, 310) after the sutures (322) have been tied.Finally, FIG. 3D shows the application of a supporting or buttressing“annuloplasty” ring (362). The valve should now be competent.

FIGS. 4A-4F are examples of simulating a mitral valve repair procedureusing computational modeling in accordance with various embodiments ofthe present disclosure. In this case, the computational modelcorresponds roughly to the steps of the operation illustrated in FIGS.3A-3D. FIG. 4A shows the mitral valve and left ventricle prior to thevirtual surgical procedure (480). FIGS. 4B-4E show a close-up view ofthe mitral valve repair as shown through a series of actions. FIG. 4Fshows a zoomed out view summarizing the post-operative state of themitral valve repair (490). Specifically, FIG. 4B shows the mitral valveafter excision of the triangular section of the prolapsing segment. Thisreflects the condition after FIG. 3A and before FIG. 3B. In FIG. 4B, theanterior (406) and posterior (408, 410) leaflets of the mitral valve areshown. The prolapsing segment has already been excised leaving atriangular defect (412). The edge of the remaining leaflet is labeledwith the arrow (404). FIG. 4C corresponds to FIG. 3B. In FIG. 4C,virtual sutures (422) are seen in place and now bridge the defect in theposterior leaflet. Similar to FIG. 3C, FIG. 4D shows the repair afterthe leaflet sutures have been virtually tied (422) bringing the edges ofthe posterior leaflet together. Similar to FIG. 3D, FIG. 4E showsvirtual sutures in place between a supporting annuloplasty ring and theedge of the mitral valve orifice (462). The aorta is seen (482). In FIG.4F, the ring (462) has been virtually secured in place.

FIG. 5 illustrates an example of human knee (500), in accordance withvarious embodiments of the present disclosure. Right knee (500) ispresented in surgical language and reflects a description of anatomythat may be encountered in a textbook. The undersurface of the patella,or knee cap, is shown dissected and reflected off (502). The anteriorcruciate ligament (504), patellofemoral groove (506), posterior cruciateligament (508), lateral distal femoral condyle (510), tibial or medialcollateral ligament (512), medial meniscus (514), tibial plateau (516),tibia (518), lateral meniscus (520), lateral or fibular collateralligament (522), and fibula (524) have been labeled. These are anatomicstructures of clinical importance as it generally relates to kneefunction as well as anatomy relevant to surgical operations as well asnon-surgical invasive procedures. This figure also illustrates anexample of information that a user may provide, using surgical language,in certain embodiments of the present disclosure.

FIG. 6A illustrates a computational model of a human knee, in accordancewith various embodiments of the present disclosure. This drawing isrepresentative of a three dimensional mesh of a right knee (600) as usedfor computational simulation of knee mechanics. The mesh includes all ofthe anatomic structures of importance to the simulation task at hand. Inthis example, the patella and fibula are not required although theseanatomic structures may be described in a textbook or provided by theuser using surgical language. In some embodiments of the presentdisclosure, the patella and fibula may be included. The portions ofcomputational mesh representing the anterior cruciate ligament (604),patellofemoral groove (606), posterior cruciate ligament (608), lateraldistal femoral condyle (610), tibial or medial collateral ligament(612), medial meniscus (614), tibial plateau (616), tibia (618), lateralmeniscus (620), lateral or fibular collateral ligament (622), and fibula(624) have been labeled. These are anatomic structures of clinicalimportance as it generally relates to knee function as well as anatomyrelevant to surgical procedures as well as non-invasive interventions.For the purpose of computational simulation, anatomic structures thatare present and required for realistic and accurate results computed bythe solver module but not commonly discussed in medical textbooks may beincluded. In this example, the three dimensional mesh includesrepresentation of the transverse meniscomeniscal or anteriorintermeniscal ligament (624) even if it has not been provided by theuser.

FIG. 6B illustrates a simulated model of a human knee (660) that hasundergone a medial meniscectomy, in accordance with various embodimentsof the present disclosure. This drawing is representative of a threedimensional mesh of a right knee that has undergone a total medialmeniscectomy as used for computational simulation of knee mechanics. Themesh includes all of the anatomic structures of importance to thesimulation task at hand. In this example, the patella and fibula are notrequired although these anatomic structures may be described in atextbook or provided by the user using surgical language. In someembodiments of the present disclosure, the patella and fibula may beincluded. The portions of computational mesh representing the anteriorcruciate ligament (604), patellofemoral groove (606), posterior cruciateligament (608), lateral distal femoral condyle (610), tibial or medialcollateral ligament (612), medial meniscus (614), tibial plateau (616),tibia (618), lateral meniscus (620), lateral or fibular collateralligament (622), and fibula (624) have been labeled. These are anatomicstructures of clinical importance as it generally relates to kneefunction as well as anatomy relevant to surgical procedures as well asnon-invasive interventions. For the purpose of computational simulation,anatomic structures that are present and required for realistic andaccurate results computed by the solver module but not commonlydiscussed in medical textbooks may be included. The output of the solvermodule, indicates that the removal of the medial meniscus results in adirectional force represented by the arrows (662). There is an increasein the gap or distance between the lateral meniscus (620) and lateraldistal femoral condyle (610). In this embodiment, the output of thesolver module could be processed by the clinical translation module anddescribed in surgical language as a “varus moment.”

FIG. 7 is a flow chart illustrating an exemplary process (700) forperforming virtual surgery, in accordance with various embodiments ofthe present disclosure. First, a virtual surgery system, e.g. system100, receives (702) user input from the user interface. The user inputincludes input representing surgical operations or surgical procedures.Next, the system processes (704) the user input and utilizes the inputto generate or modify a computational model. Subsequently, the systemruns (706) simulations using the computational model in accordance withthe user input. Then, the system determines (708) results from thesimulations. In some embodiments, the results correspond to probableeffects or outcomes of performing real life surgical operations orsurgical procedures corresponding to the user input. Last, the systempresents (710) the results to the user via the user interface.

In the present disclosure, the clinical translation module determinesthe relevant output from the solver module to be provided in surgicallanguage. In some embodiments, for example in orthopedic surgery, solveroutput can be translated into surgical language to determine if anintended surgical implant fits well or does not fit well. Criteria for a“good” fit may additionally be provided. In some embodiments, as in forcardiac surgery, the solver output will be translated into surgicallanguage to describe the cardiac output, myocardial wall stress, orstroke volume as a result of a surgical operation or non-surgicalinvasive procedure. In other embodiments, the user may specify therelevant output to be reported by the solver module and the preferredtranslation into surgical language.

In some implementations, further processing of the clinical informationis performed by an information integration module which converts theclinical information into a format usable by the solver module or aformat appropriate for further processing by the clinical translationmodule. In some implementations, the conversion is performed in anautomated fashion by a computer. In some implementations, the conversionis performed in a semi-automated fashion where approval and confirmationis required. In some implementations, the confirmation is performed bythe user performing the simulation. In other implementations, theconfirmation is performed by a different user from the user performingthe simulation.

In some implementations, once the data which has been fully analyzed andprocessed by the information integration module, the clinicaltranslation module translates the steps of the surgery or procedure inthe queue into a format usable by the solver module. As an example, anexample of one surgical step in a virtual surgery is presented below.For instance, a “simple, interrupted stitch” which is the equivalent ofsticking a needle through one piece and then another and then tying thefree ends of the suture together, can be implemented by identifying theportion of the geometric mesh describing the location of the sutures,the material properties of the suture to be used, and the loadingconditions which reflect the manner in which the surgical knot isperformed. According to various embodiments, the system can simulatemultiple different types of stiches as well as different types ofcutting of tissue or altering the shape of different organs or tissues.According to various embodiments, the system can simulate multiplesurgical steps that represent one virtual surgery or many virtualsurgeries.

According to various embodiments, the virtual instructions are convertedinto an “input file” for use with the solver module. In someembodiments, the input file has coordinates for elements representing ageometric mesh, descriptions of the material properties for eachelement, and the loading conditions reflecting one or more steps of asurgery. The input file is then passed onto the solver module thatcomputes the result of the surgeon's action or actions.

According to various embodiments, the solver module outputs data in theformat of numbers describing how the coordinates of each element of themesh have changed after surgery as well as the forces, stress and strainthat affect each part of the portion of the human body to be analyzed.In some embodiments, other information relevant to the computationaloutcome of the surgery is included by the solver module. This data mayinclude information that is not in surgical language such as a largedatabase of numbers that can be very difficult for a user to interpretand understand.

According to various embodiments, the clinical translation module thenmodifies the output to reflect the next step or steps of the user queueto produce a new input for the solver module, determines that thesurgery is complete, or awaits further user input.

According to various embodiments, the clinical translation module thenconverts the numerical information and other non-surgical language fromthe solver into a clinically useful presentation of the outcome of thesurgery using surgical language. In some embodiments, this can be agraph of pressure on the surface of a portion of the joint, acolor-coded picture or video, a description of the change in a parametersuch as stroke volume, or even a simple pass/fail statement. In someembodiments, the information is delivered to the surgeon so that he/shecan determine the best surgical plan for the patient.

In some embodiments, the system translates the output from the solverinto surgical language using touch, e.g. the tactile resistance of asurgical screwdriver traveling through bone of different density, avibration on a surgical instrument, or heat of surgical saw.

In some embodiments, the system translates the output from the solverinto surgical language using sound, e.g. an audible tone, the change inpitch of a surgical drill going from a low to high density portion ofbone, the change in rate and rhythm of a beating heart.

In some embodiments, the system can be used to train surgeons onsurgical procedures. In some embodiments, the system can be designedsuch multiple simulations with different outcomes can be accessed by auser. The system can also be designed to only allow a limited selectionof surgical procedures or operations.

In some embodiments, the system is used prior to the actual surgery orprocedure to provide the outcome of the virtual surgery in surgicallanguage before the actual surgery or procedure is performed.

In some embodiments, the system is used during the actual surgery orprocedure to provide an on-going predictive outcome of the surgery asthe surgery or procedure is being performed.

In some embodiments, the system is used after the actual surgery orprocedure is complete to provide a retrospective comparison between thetrue results and the predicted results.

In some embodiments, the system is used in a combination of time periodsbefore, during, and after surgery.

In some embodiments, the system is used to develop, optimize, orotherwise evaluate a device or instrument intended for use as a part ofthe surgery.

In some embodiments, the software used for computational modeling can beLS-DYNA. LS-DYNA, is a finite element software, originally designed bymilitary scientists. It allows computers to solve a very large set ofpartial differential mathematical equations on supercomputers. LS-DYNAonly accepts input files in its own proprietary format and outputsnumbers and data, which may be difficult to interpret by surgeons. Thefollowing represents an exemplary input file representing a cube ofaluminum containing a geometric mesh of one element and eight nodes, onematerial property consistent with aluminum, and one loading condition inLS-DYNA:

*KEYWORD *TITLE Example of aluminum cube deformation $ output parameters*CONTROL_TERMINATION  1. *DATABASE_BINARY_D3PLOT .1 $ geometric mesh*PART aluminum_cube 1 1 1 *SECTION_SOLID 1 *NODE 1 0 0 0 7 7 2 1 0 0 5 03 1 1 0 3 0 4 0 1 0 6 0 5 0 0 1 4 0 6 1 0 1 2 0 7 1 1 1 0 0 8 0 1 1 1 0*ELEMENT_SOLID 1 1 1 2 3 4 5 6 7 8 $ material properties *MAT_ELASTIC1 2700. 70.e+09 .3 $ loading conditions *LOAD_SEGMENT 1 1 0 5 6 7 8*DEFINE_CURVE 1 0 0 1 70.e+05

In some embodiments, the input required for realistic surgicalsimulation requires more than one element or node to be described. Inone example, a computational model of a right knee may have over 88,000nodes and over 74,000 elements. The amount of input is dependent on thecomplexity of the anatomy being simulated and the virtual surgery to beperformed and therefore does not have an upper or lower limit.

In some embodiments, the solver module can be LS-DYNA. The output fromthe solver module describing the coordinates of each element of the meshthat have changed after simulation as well as the forces, stress andstrain is a large database of numbers which requires effort tointerpret. The database of numbers can be thousands to pages to hundredsof thousands of pages. The amount of output is dependent on thecomplexity of the anatomy being simulated and therefore does not have anupper or lower limit The following represents an exemplary output of thenumerical data produced by LS-DYNA for a representing a cube of aluminumcontaining a geometric mesh of one element and eight nodes, one materialproperty consistent with aluminum, and one loading condition:

 *KEYWORD $TIME_VALUE = 9.9999309e−001 $STATE_NO = 11 *ELEMENT_SOLID1 1 1 2 3 4 5 6 7 8 *NODE 1 0.0000000e+000 0.0000000e+000 0.0000000e+0002 1.0000300e+000 0.0000000e+000 0.0000000e+000 3 1.0000300e+0001.0000300e+000 0.0000000e+000 4 0.0000000e+000 1.0000300e+0000.0000000e+000 5 0.0000000e+000 0.0000000e+000 9.9990004e−001 61.0000300e+000 0.0000000e+000 9.9990004e−001 7 1.0000300e+0001.0000300e+000 9.9990004e−001 8 0.0000000e+000 1.0000300e+0009.9990004e−001 *INITIAL_VELOCITY_NODE  2 −9.620E−6 0.0 0.0  3 −9.620E−6−9.620E−6 0.0  4  0.0 −9.620E−6 0.0  5  0.0 0.0 −2.095E−5  6−9.620E−6 0.0 −2.095E−5  7 −9.620E−6 −9.620E−6 −2.095E−5  8  0.0−9.620E−6 −2.095E−5 *END $NODAL_DISPLACEMENT 1 0.0000000e+0000.0000000e+000 0.0000000e+000 2 3.0040741e−005 0.0000000e+0000.0000000e+000 3 3.0040741e−005 3.0040741e−005 0.0000000e+000 40.0000000e+000 3.0040741e−005 0.0000000e+000 5 0.0000000e+0000.0000000e+000 −9.9956989e−005 6 3.0040741e−005 0.0000000e+000−9.9956989e−005 7 3.0040741e−005 3.0040741e−005 −9.9956989e−005 80.0000000e+000 3.0040741e−005 −9.9956989e−005 $NODAL_RESULTS $RESULT OF 12.1125E−36  2 0.0  37.9903E−36  4 0.0  53.6434E−44  64.2039E−44 74.6243E−44  85.1848E−44

In some embodiments, the output required for realistic surgicalsimulation requires more than one element or node to be described. Inone such example, a computational model of a right knee may have over88,000 nodes and over 74,000 elements. The amount of output is dependenton the complexity of the anatomy being simulated and the virtual surgeryto be performed and therefore does not have an upper or lower limit.

FIG. 8 is a block diagram illustrating an example of a computer systemcapable of implementing various processes described in the presentdisclosure. The system 800 typically includes a power source 824; one ormore processing units (CPU's) 802 for executing modules, programs and/orinstructions stored in memory 812 and thereby performing processingoperations; one or more network or other communications circuitry orinterfaces 820 for communicating with a network 822; controller 812; andone or more communication buses 814 for interconnecting thesecomponents. In some embodiments, network 822 can be the anothercommunication bus, the Internet, an Ethernet, an Intranet, other widearea networks, local area networks, and metropolitan area networks.Communication buses 814 optionally include circuitry (sometimes called achipset) that interconnects and controls communications between systemcomponents. System 800 optionally includes a user interface 804comprising a display device 806, a keyboard 808, and a mouse 810. Memory812 includes high-speed random access memory, such as DRAM, SRAM, DDRRAM or other random access solid state memory devices; and may includenon-volatile memory, such as one or more magnetic disk storage devices,optical disk storage devices, flash memory devices, or othernon-volatile solid state storage devices. Memory 812 may optionallyinclude one or more storage devices 816 remotely located from the CPU(s)802. Memory 812, or alternately the non-volatile memory device(s) withinmemory 812, comprises a non-transitory computer readable storage medium.In some embodiments, memory 812, or the computer readable storage mediumof memory 812 stores the following programs, modules and datastructures, or a subset thereof:

-   -   an operating system 840 that includes procedures for handling        various basic system services and for performing hardware        dependent tasks;    -   a file system 844 for storing various program files;    -   a virtual surgery application module 846 for a user to provide        clinical imaging and other clinical information to the clinical        translation module, to make modifications to virtual anatomy, to        review the output from the solver module.    -   a solver module 856 for receiving input from a clinical        translation module 860 and computes the outcome of a surgery        defined by one or more geometric meshes, material properties,        and loading conditions and provides that output to the clinical        translation module using methods that represent true physical        phenomena with sufficient accuracy to reflect clinical reality.    -   an information integration module 858 that processes clinical        imaging and other clinical information to generate or modify a        geometric mesh, a material property or a loading condition for        use with solver module 856 or for use with a clinical        translation module 860.    -   a clinical translation module 860 that receives input from and        provides output to the virtual surgery application module 846,        that provides input to and receives output from the solver        module 856, that provides and/or receives input and/or output to        the information integration module and performs translation to        and from surgical language.    -   and a user database 862 for storing user information, for        example first and last name, passwords, contact information, and        billing or subscription information.

Virtual surgery application module 846 may include the followingsubmodules, or a subset thereof:

-   -   a digital anatomic model module 850 containing the following        fields and subfields, or a subset thereof: geometric mesh (mesh        ID, mesh elements, nodes, parts, sections), material property        (material property ID, constitutive equation, constant [1-N]),        loading conditions (loading condition ID, loading condition        type, direction, magnitude, constant [1-N]). Multiple geometric        meshes exist. In some embodiments, these can be divided into        parts and sections. Multiple parts can be assigned to a single        mesh ID and can represent a portion of anatomy. Multiple        sections can be assigned to a single part ID. Multiple elements        can be assigned to a single section ID. Multiple nodes can be        assigned to a single element ID. In various embodiments, these        subsets describe the appearance of anatomy and allows each        relevant component of the anatomy to be uniquely assigned        material properties and loading conditions as appropriate.    -   a user action queue module 852 containing the following fields        and subfields, or a subset thereof: action ID, queue position,        action, time_of_action. Each action performed by the user is        assigned an action ID. Multiple actions can share a single queue        position. The action can be modification of anatomy through        surgical language or direct interaction with a geometric mesh,        material property or loading condition. The action can also be a        request for output from the system through surgical language or        in terms of a geometric mesh, material property and other data        associated physical properties. The time of action is combined        with queue position to precisely determine when an action is        simulated.    -   an additional clinical information module 854 containing the        following fields and subfields, or a subset thereof:        clinical_info_ID, clinical_data [1-N], datatype. Each item of        clinical information is assigned a unique ID. The clinical_data        can be in arbitrary text or binary format with the datatype        defining the type of data.

Each of the above identified elements may be stored in one or more ofthe previously mentioned memory devices, and corresponds to a set ofinstructions for performing a function described above. The aboveidentified modules or programs (i.e., sets of instructions) need not beimplemented as separate software programs, procedures or modules, andthus various subsets of these modules may be combined or otherwisere-arranged in various embodiments. In some embodiments, memory 812 maystore a subset of the modules and data structures identified above.Furthermore, memory 812 may store additional modules and data structuresnot described above.

Although FIG. 8 shows a “virtual surgery simulation system,” FIG. 8 isintended more as functional description of the various features whichmay be present in a set of servers than as a structural schematic of theembodiments described herein. In practice, and as recognized by those ofordinary skill in the art, items shown separately could be combined andsome items could be separated. For example, some items shown separatelyin FIG. 8 could be implemented on single servers and single items couldbe implemented by one or more servers. The actual number of servers usedto implement a virtual surgery simulation system and how features areallocated among them will vary from one implementation to another, andmay depend in part on the amount of data traffic that the system musthandle during peak usage periods as well as during average usageperiods.

According to various embodiments, the system includes software thatimplements a graphical user interface that allows surgeons to describetheir surgical plan on a patient, whether it is a cardiac surgery ororthopedic surgery patient, using surgical language they are familiarwith. Similarly the system will incorporate software that presents thesolution or outcome of the surgery in a format using surgical language.

The foregoing description, for purpose of explanation, has beendescribed with reference to specific embodiments. However, theillustrative discussions above are not intended to be exhaustive or tolimit the present disclosure to the precise forms disclosed. Manymodifications and variations are possible in view of the aboveteachings. The embodiments were chosen and described in order to bestexplain the principles of the present disclosure and its practicalapplications, to thereby enable others skilled in the art to bestutilize the present disclosure and various embodiments with variousmodifications as are suited to the particular use contemplated.

What is claimed is:
 1. A method comprising: determining a computationalmodel associated with a surgical scenario, wherein the computationalmodel comprises one or more of: a geometric mesh, one or more materialproperties, and one or more loading conditions; receiving, via a userinterface, a user input, wherein the user input comprises one or moresurgical operations or non-surgical invasive procedures; determining,based on the user input one or more modifications to the computationalmodel, the geometric mesh, the one or more material properties, or theone or more loading conditions; determining, based on the one or moremodifications and one or more simulations, one or more mathematicalrepresentations of one or more surgical outcomes; determining one ormore simulation results from the one or more simulations; determining anideal result associated with the one or more surgical operations ornon-surgical invasive procedures; comparing the ideal result and the oneor more simulation results; converting at least a portion of one or moreof the one or more simulation results and the ideal result into surgicallanguage; and presenting, via the user interface, the converted at leasta portion of the one or more simulation results and the comparison ofthe ideal result and the one or more simulation results to the user viathe user interface.
 2. The method of claim 1, further comprisingprocessing the user input, wherein processing the user input comprisessending pre- and post-processing data to a solver module.
 3. The methodof claim 1, wherein the computational model is a finite element model.4. The method of claim 1, wherein the user input includes input from akeyboard, mouse, camera, microphone, tablet, cellular phone, anyhand-held device, or any haptic device capable of performing motions orfunctions representing surgical operations or other non-surgicalinvasive procedures that effect anatomic structures.
 5. The method ofclaim 1, wherein the user input is sent via a web browser or anyapplication with access to a communications network.
 6. The method ofclaim 2, wherein processing the user input comprises performing one moreactions in a queue, utilizing the user input to generate or modify acomputational anatomic model, the computational anatomic model beingdivided into one or more parts including a geometric mesh, materialproperties, and loading conditions.
 7. The method of claim 1, whereinthe user input is pre-processed before being received.
 8. The method ofclaim 1, further comprising converting clinical imaging or information,such as blood pressure, height, weight, and lab results, into data andrepresenting the data in a computational model including a geometricmesh, material properties, and loading conditions.
 9. The method ofclaim 1, wherein the user input includes surgical language andprocessing the user input includes converting, via a clinicaltranslation module, the surgical language to changes or discrete valuesin a geometric mesh, material properties, or loading conditions of acomputational model.
 10. The method of claim 1, wherein converting theat least a portion of the one or more of the one or more simulationresults and the ideal result into surgical language comprises convertingoutput geometric mesh, the one or more material properties, or otherdata with associated physical properties into surgical language.
 11. Themethod of claim 1, further including validating user informationsubmitted from a user system to a clinical system.
 12. A systemcomprising: a user device with a user interface; and a computer,including a processor and memory, configured for: determining acomputational model associated with a surgical scenario, wherein thecomputational model comprises one or more of: a geometric mesh, one ormore material properties, and one or more loading conditions; receiving,via a user interface, a user input, wherein the user input comprises oneor more surgical operations or non-surgical invasive procedures;determining, based on the user input, one or more modifications to thecomputational model, the geometric mesh, the one or more materialproperties, or the one or more loading conditions; determining, based onthe one or more modifications and one or more simulations, one or moremathematical representations of one or more surgical outcomes;determining one or more simulation results from the one or moresimulations; determining an ideal result associated with the one or moresurgical operations or non-surgical invasive procedures; comparing theideal result and the one or more simulation results; converting at leasta portion of one or more of the one or more simulation results and theideal result into surgical language; and presenting, via the userinterface, the converted at least a portion of the one or moresimulation results and the comparison of the ideal result and the one ormore simulation results to the user via the user interface.
 13. Thesystem of claim 12, wherein the system is further configured to processthe user input, wherein processing the user input comprises sending pre-and post-processing data to a solver module.
 14. The system of claim 13,wherein processing the user input comprises performing one more actionsin a queue, utilizing the user input to generate or modify acomputational anatomic model, the computational anatomic model beingdivided into one or more parts including a geometric mesh, materialproperties, and loading conditions.
 15. The system of claim 12, whereinthe user input includes input from a keyboard, mouse, camera,microphone, tablet, cellular phone, any hand-held device, or any hapticdevice capable of performing motions or functions representing surgicaloperations or other non-surgical invasive procedures that effectanatomic structures.
 16. The system of claim 12, wherein the system isfurther configured to convert clinical imaging or information, such asblood pressure, height, weight, and lab results, into data andrepresenting the data in a computational model including a geometricmesh, material properties, and loading conditions.
 17. The system ofclaim 12, wherein the user input includes surgical language andprocessing the user input includes converting, via a clinicaltranslation module, the surgical language to changes or discrete valuesin a geometric mesh, material properties, or loading conditions of acomputational model.
 18. The system of claim 12, wherein the system isfurther configured to convert the at least a portion of the one or moreof the one or more simulation results and the ideal result into surgicallanguage by converting an output geometric mesh, the one or morematerial properties, or other data with associated physical propertiesinto surgical language.
 19. The system of claim 12, further includingvalidating user information submitted from a user system to a clinicalsystem.
 20. A non-transitory computer readable medium storingprocessor-executable instructions that, when executed by one or moreprocessors, cause the one or more processors to: determine acomputational model associated with a surgical scenario, wherein thecomputational model comprises one or more of: a geometric mesh, one ormore material properties, and one or more loading conditions; receive,via a user interface, a user input, wherein the user input comprises oneor more surgical operations or non-surgical invasive procedures;determine, based on the user input, one or more modifications to thecomputational model, the geometric mesh, the one or more materialproperties, or the one or more loading conditions; determine, based onthe one or more modifications and one or more simulations, one or moremathematical representations of one or more surgical outcomes; determineone or more simulation results from the one or more simulations;determine an ideal result associated with the one or more surgicaloperations or non-surgical invasive procedures; compare the ideal resultand the one or more simulation results; convert at least a portion ofone or more of the one or more simulation results and the ideal resultinto surgical language; and present, via the user interface, theconverted at least a portion of the one or more simulation results andthe comparison of the ideal result and the one or more simulationresults to the user via the user interface.